1. Technical Field
The present invention relates generally to an apparatus and method for correcting a disparity map and, more particularly, to an apparatus and method for correcting a disparity map, which removes the noise of the disparity map attributable to stereo matching and also fills in holes attributable to occlusion using information about the depth of a 3-dimensional (3D) model produced in a preceding frame of a current frame, thereby improving a disparity map and depth performance and providing high-accuracy depth information to an application to be used.
2. Description of the Related Art
The human visual system has been known to obtain distance information by appropriately matching two images obtained at different positions. Stereo matching corresponds to a field related to computer vision that seeks to automate the ability of the human visual system to extract the distance. This method has been widely used in medical imaging, factory automation and map production because it is more effective than a method of measuring the distance as a function of the traveling time and speed of light by using ultrasonic waves and a laser as a light source and because it is less restricted by the actual application environment.
The results of stereo matching are output as a disparity map. The disparity map is a map where pixel-based positional disparity values are plotted at corresponding coordinates based on one of left and right images. The disparity map is also called a depth map. The disparity map may be converted into distances using a formula, and such distances may be changed into depth information.
Although there are a variety of stereo matching methods, an error is generated in a disparity map because no stereo matching method is perfect. Many errors are caused by limitations in the algorithms themselves or problems with the acquired image data. For example, occlusion, in which an object is seen in only one of the left and right images, results from the limitations of an algorithm itself, and noise, in which an object is seen both on the left and right images but the pixel color values of the object are different on the left and right images, results from a problem with the acquired image data. Saturation attributable to the reflection of light off the image may be generated in either case. Such errors need to be corrected because they may lead to inaccurate depth information.
A conventional method for solving the above problems includes a method of correcting errors using the adjacent disparity values of a current frame. However, this method is problematic because any error stemming from a portion where an adjacent disparity value is considerably different from a disparity value in a portion where an error is generated (e.g., a boundary portion) cannot be accurately corrected.